Data Scientist transforming complex data sets into actionable insights at Booz Allen. Collaborating with clients and developing algorithms to address global challenges with real - world impact.
About the role
- Lead Data Scientist driving the development of personalization and recommendation systems at GoPay. Collaborating with Product and Engineering teams to deploy scalable ML pipelines.
Responsibilities
- Drive the development of GoPay’s personalization and recommendation systems to deliver relevant offers, merchants, and experiences.
- Define the technical direction for recommendation models.
- Work closely with Product and Engineering to deploy scalable ML pipelines.
- Lead experimentation to measure business impact.
- Continuously improve models in production.
- Mentor data scientists.
- Align personalization efforts with GoTo’s broader roadmap.
Requirements
- 6–8 years of relevant experience in applied data science or machine learning roles.
- Proficiency in Python, and familiarity with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.
- Solid understanding of ML fundamentals including supervised learning, ranking, embeddings, and evaluation metrics.
- Hands-on experience in recommender systems, personalization, search, or ranking models is strongly preferred.
- Experience working with large-scale datasets using platforms such as Spark, MaxCompute (MC), or other distributed data environments.
- Strong analytical and problem-solving skills, with the ability to translate complex data insights into actionable recommendations.
- Good communication skills to engage with cross-functional partners and present results clearly.
- Master’s or Ph.D. in a quantitative discipline (e.g., Computer Science, Statistics, Applied Mathematics, or related field) is a plus.
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